Fitting Mixtures of Erlangs to Censored and Truncated Data Using the EM Algorithm

We present a calibration procedure for fitting mixtures of Erlangs to censored and truncated data by iteratively using the EM algorithm. Mixtures of Erlangs form a very versatile, yet analytically tractable, class of distributions making them suitable for modeling purposes. The effectiveness of the proposed algorithm is demonstrated on simulated data as well as real data sets

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Year of publication:	2017
Authors:	Roel, Verbelen ; Gong, Lan ; Antonio, Katrien ; Badescu, Andrei ; Lin, X. Sheldon
Publisher:	[S.l.] : SSRN

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Extent:	1 Online-Ressource (28 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: ASTIN Bulletin, 2015, 45(3), 729-758 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments January 24, 2014 erstellt
Other identifiers:	10.2139/ssrn.2381838 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014149715